Dynatrace

FEBRUARY 8, 2021

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. They are required to understand the full story of what happened in a system.

Cloud 258

Cloud Azure Analytics AWS 258

Dynatrace

JANUARY 31, 2024

Retrieval-augmented generation emerges as the standard architecture for LLM-based applications Given that LLMs can generate factually incorrect or nonsensical responses, retrieval-augmented generation (RAG) has emerged as an industry standard for building GenAI applications.

Cache 201

Cache Azure Infrastructure Monitoring 201

Scalegrid

JANUARY 8, 2024

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making. These services are tailored to meet various business requirements.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

NOVEMBER 20, 2023

Across the cloud operations lifecycle, especially in organizations operating at enterprise scale, the sheer volume of cloud-native services and dynamic architectures generate a massive amount of data.  Using fault-tree analysis, this kind of AI provides critical detail about how its models arrive at a given conclusion. What is AIOps?

AWS 205

AWS Artificial Intelligence Analytics Cloud 205

ScaleOut Software

AUGUST 5, 2020

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

Analytics 69

Analytics Azure Processing Speed 69

Dynatrace

SEPTEMBER 13, 2023

And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem.

AWS 243

AWS Efficiency Azure Cloud 243

Dynatrace

JANUARY 5, 2022

In recent years, customer projects have moved towards complex cloud architectures, including dozens of microservices and different technology stacks which are challenging to develop, maintain, and optimize for resiliency. Each step is automated from provisioning infrastructure to problem analysis. from other test tools or real users).

Testing 214

Testing Open Source Metrics Infrastructure 214

Dynatrace

JUNE 15, 2023

If your app runs in a public cloud, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), the provider secures the infrastructure, while you’re responsible for security measures within applications and configurations. However, open source software is often a vector for security vulnerabilities.

Cloud 173

Cloud Open Source Architecture Monitoring 173

Dynatrace

FEBRUARY 12, 2024

The new observability app for databases from Dynatrace was built to cater to all requirements of database administrators (DBAs), from swiftly assessing database availability and performance to delving into architectural intricacies for efficient troubleshooting. It helps teams to find under or overutilized resources and components quickly.

Engineering 178

Engineering Development Infrastructure Cloud 178

Dynatrace

OCTOBER 1, 2021

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Dynatrace news. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

The Morning Paper

FEBRUARY 27, 2020

Gandalf: an intelligent, end-to-end analytics service for safe deployment in cloud-scale infrastructure , Li et al., This paper describes Gandalf, the software deployment monitor in production at Microsoft Azure for the past eighteen months plus. In Azure, most catastrophic issues happen within 1 hour after the rollout.

Analytics 68

Analytics Infrastructure Cloud Hardware 68

Dynatrace

NOVEMBER 22, 2021

Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. These tools simply can’t provide the observability needed to keep pace with the growing complexity and dynamism of hybrid and multicloud architecture.

AWS 225

AWS Lambda Artificial Intelligence Serverless 225

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

Dynatrace

APRIL 22, 2022

This gives organizations visibility into their hybrid and multicloud infrastructures , providing teams with contextual insights and precise root-cause analysis. “Dynatrace is enterprise-ready, including automated deployment and support for the latest cloud-native architectures with role-based governance,” Nalezi?ski

Cloud 165

Cloud Lambda Serverless AWS 165

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 52

Analytics Social Media Serverless Cloud 52

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

JUNE 1, 2021

Root-cause and impact analysis of application performance problems and business outcomes for faster, more reliable incident resolution. Business KPIs and user journey analysis (for example, login to check out) to optimize user experiences and provide transparency into how changes impact KPIs. User experience and business analytics.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

Dynatrace

SEPTEMBER 17, 2019

Cluster and container Log Analytics. MaaSS for Cloud Architects: Deployment and Architecture Validations. Validate correct architecture, configuration and deployment by looking at Service Flow! Full-stack observability. End-to-end code-level tracing. Service mash insights. End-user monitoring. 1 Validate Deployment.

AWS 127

AWS Monitoring Ecommerce Lambda 127

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. It’s not enough to just pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. To make this possible, the Azure-based streaming service hosts a real-time digital twin for each data source. What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. To make this possible, the Azure-based streaming service hosts a real-time digital twin for each data source. What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

O'Reilly

MAY 19, 2020

AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. But most Azure and GCP users also use AWS; the reverse isn’t necessarily true. However, close to half (~48%) use Microsoft Azure, and close to one-third (~32%) use Google Cloud Platform (GCP).

Cloud 141

Cloud Serverless AWS Architecture 141

High Scalability

NOVEMBER 25, 2019

Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. SOA architecture based on REST APIs. Google cloud.

Architecture 52

Architecture Cache Azure Storage 52